A gem

I just found it earlier today. So do I link here, here or perhaps here? I don’t know yet, there’s much to explore and I haven’t spent a lot of time there yet. A longish quote from one of the ‘notes’ (which has more..):

““That is, from January 1926 through December 2002, when holding periods were 19 years or longer, the cumulative real return on stocks was never negative…”

How does one engage in extremely long investments? On a time-scale of centuries, investment is a difficult task, especially if one seeks to avoid erosion of returns by the costs of active management.

‘Unit Investment Trust (UIT) is a US investment company offering a fixed (unmanaged) portfolio of securities having a definite life.’

‘A closed-end fund is a collective investment scheme with a limited number of shares’

In long-term investments, one must become concerned about biases in the data used to make decisions. Many of these biases fall under the general rubric of “observer biases” – the canonical example being that stocks look like excellent investments if you only consider America’s stock market, where returns over long periods have been quite good. For example, if you had invested by tracking the major indices any time period from January 1926 through December 2002 and had held onto your investment for at least 19 years, you were guaranteed a positive real return. Of course, the specification of place (America) and time period (before the Depression and after the Internet bubble) should alert us that this guarantee may not hold elsewhere. Had a long-term investor in the middle of the 19th century decided to invest in a large up-and-coming country with a booming economy and strong military (much like the United States has been for much of the 20th century), they would have reaped excellent returns. That is, until the hyperinflation of the Wiemar Republic. Should their returns have survived the inflation and imposition of a new currency, then the destruction of the 3rd Reich would surely have rendered their shares and Reichmarks worthless. Similarly for another up-and-coming nation – Japan. Mention of Russia need not even be made.

Clearly, diversifying among companies in a sector, or even sectors in a national economy is not enough. Disaster can strike an entire nation. Rosy returns for stocks quietly ignore those bloody years in which exchanges plunged thousands of percent in real terms, and whose records burned in the flames of war. Over a timespan of a century, it is impossible to know whether such destruction will be visited on a given country or even whether it will still exist as a unit. How could Germany, the preeminent power on the Continent, with a burgeoning navy rivaling Britain’s, with the famous Prussian military and Junkers, with an effective industrial economy still famed for the quality of its mechanisms, and with a large homogeneous population of hardy people possibly fall so low as to be utterly conquered? And by the United States and others, for that matter? How could Japan, with its fanatical warriors and equally fanatical populace, its massive fleet and some of the best airplanes in the world – a combination that had humbled Russia, that had occupied Korea for nigh on 40 years, which easily set up puppet governments in Manchuria and China when and where it pleased – how could it have been defeated so wretchedly as to see its population literally decimated and its governance wholly supplanted? How could a god be dethroned?

It is perhaps not too much to say that investors in the United States, who say that the Treasury Bond has never failed to be redeemed and that the United States can never fall, are perhaps overconfident in their assessment. Inflation need not be hyper to cause losses. Greater nations have been destroyed quickly. Who remembers the days when the Dutch fought the English and the French to a standstill and ruled over the shipping lanes? Remember that Nineveh is one with the dust.

In short, our data on returns is biased. This bias indicates that stocks and cash are much more risky than most people think, and that this risk inheres in exogenous shocks to economies – it may seem odd to invest globally, in multiple currencies, just to avoid the rare black swans of total war and hyperinflation. But these risks are catastrophic risks. Even one may be too many.

This risk is more general. Governments can die, and so their bonds and other instruments (such as cash) rendered worthless; how many governments have died or defaulted over the last century? Many. The default assumption must be that the governments with good credit, who are not in that number, may simply have been lucky. And luck runs out.”

Here’s another:

“Why IQ doesn’t matter and how points mislead

One common anti-IQ arguments is that IQ does nothing and may be actively harmful past 120 or 130 or so; the statistical evidence is there to support a loss of correlation with success, and commentators can adduce William Sidis if they don’t themselves know any such ‘slackers’, or the Terman report’s similar findings.

This is a reasonable objection. But it is rarely proffered by people really familiar with IQ, who also rarely respond to it. Why? I believe they have an intuitive understanding that IQ is a percentile ranking, not an absolute measurement.

It is plausible that the 20 points separating 100 and 120 represents far more cognitive power and ability than that separating 120 and 140, or 140 and 160. To move from 100 to 120, one must surpass roughly 20% of the population; to move from 120 to 140 requires surpassing a smaller percentage, and 140–160 smaller yet.

Similarly it should make us wonder how much absolute ability is being measured at the upper ranges when we reflect that, while adult IQs are stable over years, they are unstable in the short-term and test results can vary dramatically even if there is no distorting factors like emotional disturbance or varying caffeine consumption.

Another thought: the kids in your local special ed program mentally closer to chimpanzees, or to Albert Einstein/Terence Tao? Pondering all the things we expect even special ed kids to learn (eg. language), I think those kids are closer to Einstein than monkeys.

And if retarded kids are closer to Einstein that the smartest non-human animal, that indicates human intelligence is very ‘narrow’, and that there is a vast spectrum of stupidity stretching below us all the way down to viruses (which only ‘learn’ through evolution).”

Incidentally, the 20 percent number is somewhat off – if you assume IQ is ~N(100,15), which is pretty standard, then by going from 100 to 120 you will pass by ~40 percent of all individuals, not 20. If you don’t have a good sense of the scale here, it’s a useful rule of thumb to know that ~2/3rds of the observations of a normally distributed variable will be within one standard deviation of the mean. When you jump from 120 to 140, you pass 8,7 percent of all humans, assuming ~N(100,15), a much smaller group of people.

But yeah, as to the rest of it, I have always had some problems with figuring out how to interpret IQ differences, in terms of how differences in IQ translates to differences in ‘human computing power’. And reading the above, it makes perfect sense that I’ve had problems with this, because that’s not easy at all. I wasn’t really thinking about the fact that the variable is at least as much about ordering the humans as it is about measuring the size of the CPU. That’s probably in part because I have an IQ much lower than Gwern.

You give yourself short shrift, I think. If it helps your self-esteem, as a child I got 135 on a short Stanford-Binet; in 2008 or 2009, the Raven’s matrix-style IQ test at iqtest.dk gave me a 115; I recently took another matrix-style test for the Good Judgement Project study, but they haven’t sent me it yet (I would be surprised if it were past the 130s).

First off, your first comment here at the site got caught by the spamfilter – sorry about that. I’ll tjeck out the links that set off the filter.

Second: Welcome to the blog, do take a look around now that you’re here.

As a small side note, I guess I only just became aware that some of the menu stuff (‘Arkiver’ = ‘Archives’, ect.) is still in Danish – I’ve never really thought about that before. I’ll try to figure out if there’s an easy way to change that tonight, the main language of the blog has been English for a long time so there’s really no good reason why I should make navigating the site harder for the English-speaking readership than absolutely necessary.. [update: There was an easy way to do that. Though I still don’t know how to change the language setting of the ‘Seneste indlæg’ (‘recent posts’) menubar. Well, I’ll probably just leave that one be.]

Third, it’s actually a bit hard but I try not to let my admittedly huge amount of self-esteem (…cough, cough…, -2 on the 1-10 scale…) be impacted negatively by the intelligence of ‘(non-)random people I meet on the internet’ – it’s low by default. (Non-random) because I seem to mostly frequent the parts of the internet which are inhabited by subcultures with an average IQ above my own, which is prbly somewhere in the IQ 125 range or so given near-optimal conditions – I’m a type 1 diabetic and so IQ performance and bloodglucose levels are closely linked. I’ve never been formally tested but I don’t consider it likely I’d ever get close to 135, though the gap is perhaps (I still find gaps like these hard to conceptualize…) not as big as I’d initially thought.

Fourth, this is a neat tool if you need to work with a normal distribution in the future.

On investing: Indeed, it’s amazing (to me) how many people, including top academics and investment professionals, fall easy prey to survivorship bias, of which what is discussed is a variety. They take X securities at time T, download their historical prices/returns starting Y years back, and prove all kinds of fancy propositions. But… what about all the securities that were out there in time T-Y that are not around any more? How did we get rid of them for our analysis without a magic crystal ball? You’ve just proven that with perfect foresight, something is true – well, okay, fair enough (or even fascinating), but since perfect foresight is, ahem, problematic, what is the practical value of your research? A good half of my time as a data miner is spent on “beautfying” my data – replenishing incomplete data series (rather than just excluding them from my analyses). It’s tedious grunt work – locating alternative sources of data, verifying comparability, normalizing where comparability is deficient, etc. – but unless you do it, how different are you from the anecdotal physicist who, when asked to develop a winning strategy for horse-betting, solved the problem for a spherical horses in vacuum? [I’ll spare you my pains in fortifying my models so that they can handle “divisions by zero” (or worse, divisions by “null”) where such “beautified” data is used in computations.]

On IQ: May I humbly recommend this video by Neil deGrasse Tyson? Insights like this one, which he kindly shares, are the reason he’s one of the few people whom I’d buy a beer any day.

You’ve (I think it was you, but perhaps it was another commenter here, I’m not completely sure) linked to the Tyson video before, I remember having watched it at some point in the past. Still good. Incidentally, reading stuff like ‘The Human Past‘, which I’ve blogged previously here and here, makes you much more conscious about the heritage we share with chimpanzees ect. and it also lets the ‘what would an ape do in this situation?’-angle come much more naturally to you. I like to keep that angle in mind because humans are so damn good at finding smart-sounding reasons for doing stupid things and sometimes the proper perspective really is to ask what Lucy‘s (great^200th) grandfather would do in this situation; if only to figure out just why the ‘solution’ ‘your brain’ tells you is the right one might be suboptimal, given that, at least from what I can tell from your comment, you no longer spend most of your time climbing around in trees eating bananas for a living 🙂

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This blog is mainly a site where I keep track of and share some of the stuff I read and learn. Only a small subset of the posts on this blog deal with economics – I have diverse interests, and as the category cloud in the sidebar below illustrates this blog contains posts about all kinds of stuff: Mathematics, physics, statistics, geology, geography, health care and medicine, psychology, evolutionary biology, genetics, history, anthropology, archaeology, chess, …

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